Welcome
Welcome to CassIO
Do you want to use Apache Cassandra® with your ML/LLM/GenAI workloads, and do you want to start NOW?
This is the place for you.
Installation and usage
Installing CassIO is as simple as
pip install cassio
However, most likely you will want to use third-party frameworks, such as LangChain, that in turn use CassIO. Depending on how these frameworks are structured, they may require CassIO upfront in their sub-dependencies or you might have to manually install it.
Example
A good example is the LangChain setup outlined here:
the LangChain framework itself does not list all of the packages
it might need and it is up to the user to pick, and install,
those that will actually be needed by their application.
In fact, you can see cassio being explicitly listed in the
requirements file for these demo notebooks.
How to use this site
Don't just browse the website: you should clone the repository and start running the code examples yourself (notebooks, tutorials, full-fledged small applications). You'll find everything in this repo.
General pre-requisites
Most code examples require a Cassandra / Astra DB database. In the general setup instructions, we show how to create a free Astra DB instance out of convenience, but of course you can use any Cassandra installation, provided you adapt the few lines of code that connect to your database.
Experimental Cassandra features
Some of the features rely on the "Vector Search" capabilities, which are being added to Cassandra right now.
If you want to experiment with these, you have several options: you can build and run locally a version of Cassandra that implements these features from a pre-release branch, or you can create an Astra DB instance choosing to enable the vector capabilities, now in Public Preview.
Keep reading to find out more.
Similarly, many of the examples need access to a third-party service for LLMs and embeddings (for instance, Google's Vertex AI or OpenAI): make sure you follow the API setup to configure the necessary API Keys and other secrets for your provider of choice.
Per-framework specific setup
We cover Cassandra integrations with several ML-centric tools and frameworks: for each of them (a section of the site), there is a subdirectory with explanations and examples. The code there is stand-alone, provided you did the general setup (see above): but usually you have first to go through a framework-specific setup (covering e.g. the setup of a suitable Python environment with the right dependencies), described at the top of the section.
Example
If you want to run the sample code for LangChain follow these steps:
- clone this repo;
- do the general DB setup;
- do the local DB setup if needed;
- do the API setup;
- do the LangChain-specific setup.
At this point you can fire up Jupyter notebook and start running any of the provided notebooks. When moving on to testing another framework, only the last step will be needed.
CassIO repository
The source code is available at this location.